Evidence map›Paper›PMID 42072576›Full record

ArticleEntropy (Basel, Switzerland)2026

Dwell Time Outperforms Social and Chemical Predictors of Behavioural Transitions in Ants.

Michael Crosscombe, Ilya Horiguchi, Shigeto Dobata, Takashi Ikegami

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Michael CrosscombeDepartment of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan.ORCID 0000-0002-5287-0249
Ilya HoriguchiDepartment of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan.ORCID 0009-0001-6842-9220
Shigeto DobataDepartment of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan.ORCID 0000-0003-1586-6758
Takashi IkegamiDepartment of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan.ORCID 0000-0003-2850-4844

Funding

Japan Society for the Promotion of Science 23KF0108Japan Society for the Promotion of Science 24H00707
6 · The paper itself

Abstract

Agent-based models of collective behaviour can reproduce the macroscopic patterns observed in biological systems, yet reproducing observed behaviour does not guarantee the model captures the true underlying mechanisms. In ant colonies, for example, clustering may arise from local imitation, chemical marking of the environment, or internal physiological states. Distinguishing between these requires predictive tests at the individual level. Here, we apply regularised hazard models to trajectory data from three colonies and systematically compare candidate mechanisms. We find that neighbour-based cues alone are weak predictors of when an ant will transition between moving and resting states. A reconstructed arrestant pheromone field is similarly weak as a predictor, and combining pheromone with neighbour cues yields inconsistent results across colonies. In contrast, a simple measure of internal state, i.e., how long an ant has occupied its current state, emerges as the dominant predictor. These results suggest that the timing of behavioural transitions is primarily governed by internal dynamics, while environmental and social cues act as modulators that shape where transitions occur rather than when.

Indexed as

ant clusteringbehavioural inertiacollective behaviourdiscrete-time hazard modelsdwell timemodel comparisonPristomyrmex punctatusstigmergy

Identifiers

PMID42072576
PMCPMC13114287

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.